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GPU capacity

GPU capacity matched to a defined workload.

Monthly GPU cards and nodes for training, inference and fine-tuning, with deployment and Production Care available as separate scopes.

  • Since 2009
  • 99.9% uptime SLA
  • P1 under 15 min
A professional GPU accelerator card on a dark graphite background
Infrastructure

The GPU name is not a complete quote.

Model, precision, concurrency, memory, CPU, RAM, storage, tenancy, region, network, term and acceptance criteria determine whether an offer fits.

01

Capacity only

A fully specified monthly card or node offer for a technically ready buyer.

02

Deployment and acceptance

Drivers, runtime, workload deployment, benchmark and agreed acceptance evidence.

03

Production Care

Monitoring, incident ownership, runbooks and operating review after acceptance.

Operating boundary

A complete GPU order record.

We separate quoted supply, deployment work and recurring operations.

01

Workload fit

Model, precision, batch, concurrency, memory and throughput assumptions.

02

Complete configuration

GPU mapping, CPU, RAM, storage, tenancy, region, network and operating environment.

03

Commercial state

Monthly minimum, stock timestamp, quote expiry, term, tax and payment timing.

04

Acceptance

What proves the capacity and deployed workload are ready for handoff.

Commercial model

Monthly per-GPU-card or node billing.

Capacity is prepaid and confirmed for the quoted term. Deployment and operations appear as separate service lines.

  • One-month minimum
  • No hourly product
  • Current capacity and quote expiry confirmed before order
Start with the workload

Tell us what runs and where ownership breaks down.